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Self-calibration of a binocular vision system based on a one-dimensional target

机译:基于一维目标的双目视觉系统的自校准

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This paper proposes a method of self-calibration of a binocular vision system based on a one-dimensional (1D) target. This method only needs a 1D target with two feature points and the distance between the two points is unknown. During the process of computation, the distance value can be set an arbitrary value which is near the actual distance value. Using the method proposed in this paper, we can get the parameters of the binocular vision system including internal parameters of the two cameras and the external parameters (but there exists a non-zero scale factor in the translation vector which is connected to the initial distance value we set), the distortion parameters of cameras and the threedimensional coordinates of the two points in different positions. In this paper, we determine theoretically that the initial distance value will not influence the results, and also the results of numerical simulation and experiment example are shown to demonstrate the method. Most importantly, this method is insensitive to the initial distance value, and it is the biggest advantage. In a practical application, we can use a 1D target with unknown distance to calibrate the binocular system conveniently; also we can use this method to calibrate the camera in a large field of view with a small 1D target.
机译:本文提出了一种基于一维(1D)目标的双目视觉系统的自校准方法。此方法仅需要具有两个特征点的一维目标,并且两个点之间的距离未知。在计算过程中,可以将距离值设置为接近实际距离值的任意值。使用本文提出的方法,我们可以得到双目视觉系统的参数,包括两个摄像机的内部参数和外部参数(但是平移向量中存在一个非零比例因子,该因子与初始距离有关)我们设定的值),相机的变形参数以及不同位置的两点的三维坐标。本文从理论上确定初始距离值不会影响结果,并通过数值模拟和实验实例验证了该方法。最重要的是,此方法对初始距离值不敏感,这是最大的优势。在实际应用中,我们可以使用未知距离的一维目标方便地校准双目系统。同样,我们也可以使用此方法在较小的1D目标的大视野内校准相机。

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